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Pocket Detection Protocol

The document outlines a protocol for identifying binding sites in protein structures using pocket detection tools. It includes steps for preparing the protein structure, selecting a detection tool, processing the structure, visualizing pockets, and defining binding site coordinates. Recommended tools include CASTp, DoGSiteScorer, and Fpocket, with guidance on saving pocket data for further analysis.

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23 views2 pages

Pocket Detection Protocol

The document outlines a protocol for identifying binding sites in protein structures using pocket detection tools. It includes steps for preparing the protein structure, selecting a detection tool, processing the structure, visualizing pockets, and defining binding site coordinates. Recommended tools include CASTp, DoGSiteScorer, and Fpocket, with guidance on saving pocket data for further analysis.

Uploaded by

inigobenze
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© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Pocket Detection Protocol for Binding Site Identification

Step 1: Prepare Your Protein Structure

- Get the PDB file for your target (e.g., LINGO-1, PDB ID: 2ID5 from https://www.rcsb.org).
- Clean the structure:
- Remove water molecules and unwanted chains.
- Keep only the monomer or domain of interest.
Tools: PyMOL, UCSF Chimera, or ChimeraX

Step 2: Choose a Pocket Detection Tool

Recommended Tools:
- CASTp: https://cast.engr.uic.edu (Web-based)
- DoGSiteScorer: https://proteins.plus (Web-based)
- Fpocket: https://github.com/Discngine/fpocket (Command-line)

Step 3: Upload or Process the Structure


Option A: CASTp

1. Go to CASTp (https://cast.engr.uic.edu)
2. Upload your PDB file or enter the PDB ID (e.g., 2ID5)
3. Click 'Submit'
4. Explore the list of detected pockets with volume, area, and location.

Option B: DoGSiteScorer

1. Visit https://proteins.plus and choose “DoGSiteScorer”


2. Upload your PDB structure
3. Analyze the predicted binding pockets and download the top-scoring ones

Step 4: Visualize Pockets

- Load the pocket coordinates (usually .mol2 or .pdb) into PyMOL or Chimera.
- Examine clefts or cavities suitable for ligand binding.
Step 5: Select the Most Promising Pocket

Choose based on:


- Volume and shape
- Hydrophobic/hydrophilic balance
- Druggability score (from DoGSite or SiteMap)

Step 6: Define Binding Site Coordinates (Optional)

If you're planning to dock using AutoDock Vina or screen with Pharmit:


- Identify the center (x, y, z) of the pocket
- Define the box size (in Å) to cover the site
Tools: PyMOL or AutoDockTools

Step 7: Save Pocket Data

Save pocket information for downstream tasks:


- Pharmacophore modeling
- Docking
- Visualization

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